ECNU at TREC 2015: Microblog Track

Abstract

This paper describes our participation in TREC 2015 Microblog track, which includes two tasks related to Scenario A and Scenario B. For Scenario A, we build a real-time tweet push system, which is mainly composed by three parts: feature extraction, relevance prediction and redundancy detection. Only the highly relevant and nonredundant tweets are sent to users based on the interest profiles. For Scenario B, we apply three query expansion methods, namely the web search based, the TFIDF-PRF based and the Terrier embedded PRF based. In addition, three state-of-the-art information retrieval models as the language model, BM25 model and DFRee model are utilized. The retrieval results are combined for final delivery. The experimental results in both scenarios demonstrate that our system obtains convincing performance.

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Document Details

Document Type
Technical Report
Publication Date
Nov 20, 2015
Accession Number
AD1004742

Entities

People

  • Beijing Huang
  • Bo Wang
  • Liang He
  • Qing Chen
  • Qinmin Hu

Organizations

  • East China Normal University

Tags

DTIC Thesaurus Topics

  • Automatic
  • Data Sets
  • Detection
  • Extraction
  • Feature Extraction
  • Feedback
  • Information Processing
  • Information Retrieval
  • Language
  • Mobile Phones
  • Natural Languages
  • Redundancy
  • Test And Evaluation
  • Training

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Information Retrieval

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval